Recent technological breakthroughs have provided the ability to manage and make sense of vast amounts of hitherto unrelated data – and in the process have redefined what it means to be a smart organization. Aggressive competitors recognize these new capabilities and put them to work. They don’t just gather and report information – they leverage it through business analytics.

Defining Business Analytics

Business analytics involves using sophisticated technology to bring information together and sophisticated algorithms to filter and analyze that information. The outputs can include deep understanding of the workings of the business and its connections to the marketplace, key performance indicators to drive business decisions, and dramatic improvements in the performance of the most critical business processes. With business analytics, smart organizations are using the wealth of data being collected today to create powerful new ways to perform and compete.

1. Where should we leverage business analytics?
It’s tempting to say “all over the place,” because any part of a business can benefit from more systemic creation, gathering and interpretation of information. But in most cases, you will want to focus business analytics where you already have distinctive capability – the aspect of the business where you excel and where you have chosen to compete.

For Walmart, the distinctive capability lies in an efficient supply chain. For automobile insurer Progressive, the most distinctive capability involves the pricing of risk. For the gaming industry leader Harrah’s, the chosen distinctive capability for the past several years has been customer loyalty – a departure from construction of the lavish casino and hotel facilities that some other firms have selected as the basis for competition.

Focus business analytics where you already compete. The payoff is greatest where you are playing to your strength, not where you are playing catch up.

2. Why now?
Because the technology is ready. Because your competitors are likely exploring the possibilities of analytical competition, too. Because it may take a while to come up the learning curve and realize the payoff. And because it’s always risky to be slow in recognizing and capitalizing on a fundamentally new business capability.

Taking an analytical approach to the most important and complex business problems used to take an enormous amount of time, money and effort.

Recent technological developments have lowered that threshold of investment dramatically. Today’s information management technology at last enables dissimilar databases to talk with one another and contribute their information to common repositories, and many corporations are investing in the integration and quality of their data.

Today’s sophisticated analytical tools include not only the established statistical regression and time series methods, but also statistically based machine-learning techniques that partially automate the processes of pattern recognition and prediction.

Almost every industry today – from  professional athletics to wine – features one or more organizations that are pursuing analytical competition. Even in the cement industry, the Mexican company Cemex – the third-largest global producer – is using analytics to coordinate supply chains. In industries with substantial amounts of online information, including travel and transport, financial services and e-commerce, virtually all leading players are emphasizing analytics.

3.  What's the payoff?
Most analytical competitors are leaders in their industries and quite successful in financial terms. In a study of 32 corporations with varying degrees of analytical orientation, an increased focus on analytics correlated with stronger financial performance. In another study of more than 400 firms, analytical competitors were five times more likely to be in the top-performing quintile than the bottom-performing.

The improvements in performance for analytical competitors are often dramatic. For example:

• Harrah’s has improved in every measure of financial performance since it adopted an analytical orientation, including revenues and profits, same-store sales, average hotel room rates, slot machine profit margins and, perhaps most importantly, stock price.
• Capital One has grown earnings per share by more than 20 percent each year since it went public in 1994 and has grown to be the third-largest provider of credit cards in the U.S.
• AutoZone creates an optimal portfolio mix of its product, pricing and promotional activities across all 3,300 stores by understanding and forecasting the performance of individual departments, products and categories within each store.
  Business analytics is all about anticipating the payoff in order to maximize it. So the analytics initiative succeeds if and when the business capitalizes on an opportunity that analytics reveals.

4. What information and technology do we need?
For starters, you must have high-quality, integrated data about the aspects of the business requiring analysis. Most companies today do not lack for sufficient amounts of data, but many still suffer from a lack of integration (Can the information be used together?) – and a lack of quality (How well does the data measure and represent the business phenomena that you want to analyze?) Without good data, you simply can’t do good analytics.
 
Key technology components:

• Integrated analytical and reporting software – crunches the data and reports the results.
• Data integration and data quality software – moves, cleans and enhances the data.
• Data warehouse/data marts – keep the data in a place to perform analysis.
• Scalable servers, storage and networks – make it possible to get results quickly and share them widely.

The most common issue relative to analytical information and technology is having too much of it scattered about. Large organizations typically have multiple business intelligence software packages installed in different functions across the enterprise. They have multiple data warehouses. They have multiple versions of data, even around key business entities like customers. And they lack an overall technology architecture both complete and flexible enough to organize and manage information and technology assets as an agile enterprise platform.

5.  What kind of people do we need?
You’ve got to have trained and skilled analytical people to do analytical work – and to succeed in analytical competition. There are three levels of analytical people to consider:

• Analytical professionals. Most successful analytical competitors have a core cadre of people, often Ph.D.s, who design and conduct experiments and tests, define and refine analytical algorithms, and perform data mining and statistical analyses on key data.
• Analytical semiprofessionals. They can do substantial amounts of modeling and analysis using spreadsheets or visual analysis tools, but are unlikely to develop sophisticated new algorithms or models.
• Analytical amateurs. The employees who do the day-to-day work of the business also need to understand something of the analytical basis for operations and decisions. For example, if a lodging chain employs sophisticated analytics for revenue management, those who quote room prices need to understand, at least to some degree, how processes are derived and when they can be overridden.

The most critical role, however, is the analytical manager, who can focus the work of analytical professionals. These managers must be intimately familiar with the business, experienced with analytical applications, and knowledgeable enough to credibly lead the analytical professionals

6. What roles must senior executives play?
Another prerequisite for analytical competition is committed senior executives who provide the passion and the resources to drive their organizations in an analytical direction. In virtually every firm that has determined to leverage analytics, the CEO and senior management team set an analytical strategy in the first place and then continually pushed it forward.

Meanwhile, other executives play vital roles in analytical competition:

• Chief financial officers. Support an analytical project with financial processes, information and staff; may advise the project or may own the project if it centers on the financial structure and management of the enterprise.
• Chief information officers. Provide technology and access to the company’s databases, including insight into their structure and the quality of their data. CIOs may support or play other roles, including catalyst, architect and business/financial analyst.
• Functional executives. Lead the business function or process in question and are usually responsible for specifying the capabilities of key information systems.
• Project leaders. Lead the charge day-to-day, have real expertise in the business process and are conversant in analytical technology and methods.

Getting and Staying Ahead

Analytical competitors that are successful over the long run keep working at it – they are never finished and can hardly rest on their laurels. Analytical firms must continue to invest in new capabilities and broaden the basis of competition by extending analytics to different business functions and units. They must explore new metrics. They must learn the lessons from successful and unsuccessful business experiments and embed the learning into ongoing and automated business processes. And they must, of course, monitor and respond to competitors who will constantly challenge an analytically derived lead.